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This study investigates factors affecting the Blaine number, including type, shape, and size distribution of the grains, d80 effect, and retention time of materials in the mill. Samples were taken from different locations in production lines of the Golgohar and Chadormalu plants in Iran. For iron minerals, Davis tube tests were performed in four stages to assess the functionality of the magnetic separator to ensure matching conditions between the plant and laboratory. The Blaine air permeability system was used to analyze the Blain number. Results indicated that the samples with the same d80 but different grain size distributions had different Blaine numbers. More specifically, increasing the percentage of grains finer than 45 microns resulted in higher Blaine numbers. Moreover, in the Golgohar Hematite and desulfurization plant, the grain size distribution was relatively fixed, and minor variations in the percentages of grains finer than 45 microns led to a change in the Blaine number, and this was consistent between different days. During the concentrate production processes, higher grades of iron concentrate and lower grades of non-iron minerals were associated with lower Blaine numbers, which could be explained by the removal of iron-free minerals finer than 45 microns, including clay. Moreover, a 1% reduction in the clay minerals led to a 400-unit reduction in the Blaine number. Several samples of hematite concentrate and clay minerals with the same grain size distribution were analyzed to investigate the influence of density and the shape of grains on the Blaine number of magnetite concentrate. Here, compared to magnetite and hematite with irregular shapes, plate-shaped clay minerals showed higher Blaine numbers. Moreover, when the feed of the magnetic separator was grinded, the reduction in the grain size increased the Blaine number. In the Chadormalu plant, a retention time of 4.5 minutes in the mill was associated with the highest Blaine number as well as the least recovery of phosphorous minerals.

The determination of grain size distribution in alluvial channels plays a crucial role in understanding fluvial dynamics and processes (e.g., hydraulic resistance, sediment transport and erosion, and habitat suitability). However, to determine an accurate distribution, tremendous field efforts are often required. Traditionally, the grain size distribution of channel beds have been obtained by manually counting a set of randomly selected stones (the “pebble count”). Based on this elementary principle, many authors have proposed different adaptations to overcome weaknesses and problems with the original method; with the development of digital technology, photographic methods have been developed in order to significantly reduce the time spent in the field. Two of these “image-assisted” methods include Automated Grain Sizing, AGS, and Manual Photo Sieving, MPS. In this study, AGS and MPS were applied under ideal laboratory conditions, to be used as reference, and in two field conditions with different degrees of difficulty in terms of visual determination of the grain size distribution; these included an artificial unlined channel and two natural mountainous streams. The results were compared with those obtained with the pebble-count method. In general, strong agreement between the methods was found when they were applied under favorable conditions (”the laboratory”), and the differences between the image-assisted and pebble count methods were similar to those found in previous studies. Despite being more time consuming, MPS was deemed preferable to AGS when conditions are not optimal; in these cases, the time spent on image elaboration significantly increased in the AGS method (approximately three-fold), but the estimation error of the median grain size decreased by approximately 37%. The use of image-assisted analysis has proven to be robust for characterizing sediment in watercourse beds and reducing fieldwork time, but because field conditions can significantly affect the accuracy of results, the method choice must be carefully considered. [ABSTRACT FROM AUTHOR]

The shear modulus at small-strain, G is a maximum value of shear modulus for a given stress state and void ratio, and is a key parameter to evaluate the dynamic response of geotechnical structures. However, the laboratory testing procedures for determining G are time-consuming, cumbersome and require elaborate equipment especially for unsaturated soil samples. A semi-empirical model is proposed in this paper that can be used to estimate the variation of G with respect to matric suction for non-plastic sandy soils (i.e. I = 0 %). The proposed model uses the Soil-Water Characteristic Curve ( SWCC) and the shear modulus at saturation condition along with two fitting parameters ζ and ξ. The proposed model permits estimation of the variation of G with respect to matric suction over different zones of the SWCC (i.e. boundary effect, transition, and residual zones) for various non-plastic sandy soils. The fitting parameters ζ and ξ required for the proposed semi-empirical model can be estimated from simple relationships derived from the grain size distribution curve. [ABSTRACT FROM AUTHOR]

Abstract: Approx. 120 resonant column (RC) tests with additional P-wave velocity measurements using piezoelectric elements have been performed on 19 clean quartz sands with piecewise linear, gap-graded, S-shaped or other smoothly shaped grain size distribution curves. For each material different pressures and densities were tested. It is demonstrated that the extended empirical equations for the small-strain constrained elastic modulus proposed by the authors in an earlier paper work well also for most of the more complex grain size distribution curves tested in the present study. These equations considering the influence of the uniformity coefficient of the grain size distribution curve were developed based on the data from tests on linear gradations. A further improvement of the prediction for the more complex grain size distributions can be achieved if the correlation equations are applied with a specially defined average inclination of the grain size distribution curve. Such an improvement is demonstrated not only for the small-strain constrained elastic modulus, but also for small-strain shear modulus, modulus degradation and Poisson's ratio. [Copyright &y& Elsevier]

The modulus degradation curves, , and the damping ratio, , of 27 clean quartz sands with specially mixed grain size distribution curves were measured in approximately 280 resonant column tests. For each material, tests with various pressures and densities were performed. Based on the test data it is demonstrated that the shear modulus degradation is larger for higher values of the uniformity coefficient, , while it is rather independent of the mean grain size, . The observed dependence of curves is not adequately described by common empirical equations because these equations were developed based on tests on uniform granular materials. To consider the influence of the uniformity coefficient, the paper proposes correlations of the parameters of the common empirical equations with . Good agreement between the prediction of the extended empirical equations and the experimental data collected from the literature is demonstrated. Furthermore, the test data reveal that the curves of damping ratio, , and the threshold shear strain amplitude indicating the onset of residual deformation accumulation, , are rather independent of and . The threshold shear strain amplitude at the onset of modulus degradation, , slightly decreases with increasing values of and . [ABSTRACT FROM AUTHOR]

Abstract: The paper presents an experimental study on the influence of the grain size distribution curve on dynamic soil properties. More than 160 resonant column tests with additional P-wave measurements have been performed on 27 different grain size distribution curves of a quartz sand. While the small-strain shear modulus G max has been discussed by Wichtmann and Triantafyllidis the present paper focusses on P-wave velocity v P , on the small-strain constrained elastic modulus M max and on Poisson''s ratio . It is demonstrated that while v P and M max do not significantly depend on mean grain size d 50 in the investigated range, they decrease with increasing coefficient of uniformity C u =d 60/d 10 of the grain size distribution curve. Poisson''s ratio does also not depend on d 50 but increases with increasing C u . An empirical formula similar to Hardin''s equation has been developed for M max, considering the influence of the grain size distribution curve. It predicts quite well the experimental data. [Copyright &y& Elsevier]